Confluent

Prior to developing the Unified Data Platform, Alight integrated back-end information within a web portal or a mobile app, for example. This approach had several drawbacks, particularly in the areas of performance, cost, and time-to-market for new solutions.They needed to handle large-scale data changes based upon near-time or real-time events in the system so that they could refresh the cache on-demand with subsecond response times.After further research, discussions with partners, vendors, and others in the industry; and some proof-of-concept (POC) projects the team was ready to move forward with their choice: Apache Kafka.

通过减少集成系统所需的时间和精力，推动国家数字银行计划和企业范围的数字化转型

Deliver real-time analytics for cloud-based communications services in a mission-critical, multi-tenant environment.As a fast-growing multi-tenant SaaS Contact Center solution, 8×8 needed a way to rapidly and cost-effectively add new customers. To support this, the company decided it wanted a single event streaming platform for all of its customers – one that could scale quickly and easily as new customers joined.The platform needed to be multi-tenant, providing strict data separation – a key customer requirement – and it had to be highly resilient given its mission-critical nature. Robust security was also a must since 8×8 handles sensitive caller information. 

SunPower is building differentiation by creating a software offering for consumers that pairs with their SunPower Equinox® solar and SunVault™ storage systems to give consumers rich access to their own energy usage data, the ability to control their SunVault™ system, and allow SunPower to optimize its own service and offers.However, this requires SunPower to collect, aggregate, and provide access to real-time data from 6 million devices, a significant challenge and well beyond the capabilities of its legacy system.SunPower wanted to utilize the vast amount of data it generated on energy usage across its existing fleet to build more efficient products, make data more accessible and actionable by different parts of the business, and offer customers a more instantaneous energy management experience.

As the company transitioned from a scrappy disruptor to a major industry player, it began to experience issues with a monolithic application it had built when the company was started. They also experienced other issues later with synchronous REST API calls between services, after they had split the monolith into microservices.Namely, developers and data engineers couldn’t resolve issues fast enough or iterate on their search functionality with sufficient agility and were taking on a significant amount of technical debt as an increasing amount of data threatened to slow down the productivity and time to market for new features.The challenge is to create an event bus to improve data collection, event-driven communication between microservices, and data discovery for new use cases.